Multi layered image enhancement technique

ABSTRACT

A system for enhancing an input image including receiving an input image and filtering the input image with a plurality of non-linear smoothing filters providing a respective plurality of filtered outputs. The system processes a plurality of the filtered outputs with respect to at least one of another of the filtered outputs and the input image to determine a plurality of detail layers. The system filters the plurality of detail layers with a plurality of non-linear smoothing filters providing a respective plurality of smoothed layers. The system adjusts the plurality of smoothed layers in such a manner that regions closer to an edge are enhanced to a lesser extent than regions farther from an edge and combining the adjusted the smoothed layers to provide an enhanced output image.

CROSS-REFERENCE TO RELATED APPLICATIONS

None.

BACKGROUND OF THE INVENTION

The present invention relates generally to a multi-layered imageenhancement technique.

A multitude of different techniques have been developed for processingand filtering two-dimensional images and two-dimensional videosequences. In particular, many image processing techniques have beendeveloped to modify a relatively low resolution image to a relativelyhigh resolution image or otherwise enhancing the existing resolution,while maintaining image clarity without the introduction of excessiveartifacts.

If an image is blurred or degraded by a well-understood process, such asshot noise occurring during transmission, the image can usually beenhanced by developing a model of the source of degradation, thenreconstructing the original image using the model. However, in manycircumstances, a source of degradation of the image cannot be modeledand, hence, the image cannot be faithfully reconstructed. Thus, genericimage enhancement is problematic since the type of noise content thereinmay be hard to determine or otherwise characterize.

What is desired therefore is a multi-stage non-linear enhancementtechnique that is suitable for a variety of different types of noisecontent.

The foregoing and other objectives, features, and advantages of theinvention may be more readily understood upon consideration of thefollowing detailed description of the invention, taken in conjunctionwith the accompanying drawings.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

FIG. 1 illustrates an overshoot at an edge region.

FIG. 2 illustrates an exemplary multi-stage non-linear enhancementtechnique.

FIG. 3 illustrates another multi-stage non-linear enhancement technique.

DETAILED DESCRIPTION OF PREFERRED EMBODIMENT

Referring to FIG. 1, when an image enhancement technique processes anedge based region illustrated by the step like function often the sharptransitions of the edges results in an overshoot in the resultingenhanced image. The overshoot tends to become even more pronounced whenthe image enhancement technique attempts to significantly enhance theimage. When using non-linear enhancement techniques the likelihood ofintroducing significant overshoot tends to become more likely. Avoidingthe introduction of substantial overshoot, particularly along edgeregions of the image, permits the image enhancement technique tointroduce additional enhancement that would have otherwise resulted insignificant image artifacts. Moreover, the technique should becomputationally efficient so that it may be applied to image content inreal time without significant computational resources, even when using anon-linear enhancement technique.

Referring to FIG. 2, an exemplary multi-channel image detail enhancementtechnique is illustrated. A series of video input frames 200 areprovided to the image detail enhancement technique. If desired, thesystem is likewise applicable for the enhancement of a single inputimage rather than a series of images.

The input frame 200 is provided to a non-linear smoothing filter λ1 202.As a general matter, non-linear filters tend to be more effective thanlinear filters, but likewise non-linear filters tend to be moredestructive than linear filters if not suitably controlled. Thenon-linear smoothing filter λ1 202 is suitable to reduce the amount ofnoise in the image. Preferably, the non-linear smoothing filter λ1 issuitable to reduce limited levels of noise in the image, which issuitable for image content that has quite limited amounts of noise. Inthis manner, the image content is not significantly degraded as a resultof the application of the non-linear smoothing filter λ1 for imagecontent with quite limited amounts of noise. The non-linear smoothingfilter λ1 provides an output base layer λ1 204 which is the result ofthe smoothing filter.

The input frame 200 is provided to a non-linear smoothing filter λ2 210.The non-linear smoothing filter λ2 210 is suitable to reduce the amountof noise in the image. Preferably, the non-linear smoothing filter λ2 issuitable to reduce medium levels of noise in the image, which issuitable for image content that has texture based amounts of noise whichis a greater amount of noise than the quite limited amounts of noise. Inthis manner, the image content is not significantly degraded as a resultof the application of the non-linear smoothing filter λ2 for imagecontent with texture based amounts of noise. The non-linear smoothingfilter λ2 provides an output base layer λ2 212 which is the result ofthe smoothing filter.

The input frame 200 is provided to a non-linear smoothing filter λ3 220.The non-linear smoothing filter λ3 220 is suitable to reduce the amountof noise in the image. Preferably, the non-linear smoothing filter λ3 issuitable to reduce significant levels of noise in the image, which issuitable for image content that has significant amounts of noise whichis a greater amount of noise than the quite limited amounts of noise anda greater amount of noise than the texture based amounts of noise. Inthis manner, the image content is not as significantly degraded as aresult of the application of the non-linear smoothing filter λ3 forimage content with such significant amounts of noise. The non-linearsmoothing filter λ3 provides an output base layer λ3 222 which is theresult of the smoothing filter. For example, the output base layer λ3222 may resemble a cartoon image.

The input frame 200 may bypass 224 the non-linear smoothing filters 202,210, 220. In this manner, a reference image is maintained that does nothave any (or an insignificant amount) of filtering applied thereto. Inthis manner, the image content is not degraded (or insignificantlydegraded) as a result of the application of one of the non-linearsmoothing filters.

Additional non-linear smoothing filters λn may be included that havedifferent amounts of noise removal, as desired. One or more linearfilters may be included, if desired. As it may be observed, each of thedifferent non-linear smoothing filters provides a different amount ofsmoothing to the same input frame 200. In this manner, the system hasavailable to it a set of output images that have different amounts ofsmoothing applied thereto, without having to pre-process the imagecontent to determine which particular smoothing filter should be appliedat the exclusion of other smoothing filters. In addition, thearrangement of a plurality of different non-linear smoothing filters,each processing the same video frame during overlapping time periods, issuitable for parallel processing.

It is desirable to determine the amount of smoothing that was applied byeach smoothing filter. In particular, it is desirable to determine theamount of smoothing that was applied by a particular non-linearsmoothing filter relative to one or more of the other non-linearsmoothing filters and/or the original input image.

To determine the amount of smoothing applied to the input frame 224 withrespect to the output 204 of the non-linear smoothing filter λ1 202 maybe determined by using a subtraction operation 230. The output of thesubtraction operation 230 is a detail layer 1 image 240. The detaillayer 1 image 240 includes the differences between the input frame 224and the output 204 of the non-linear smoothing filter λ1 202.

To determine the amount of smoothing applied to the input frame 224 withrespect to the output 212 of the non-linear smoothing filter λ2 210 maybe determined by using a subtraction operation 232. The output of thesubtraction operation 232 is a detail layer 2 image 242. The detaillayer 2 image 242 includes the differences between the output 204 of thenon-linear smoothing filter λ1 202 and the output 212 of the non-linearsmoothing filter λ2 210.

To determine the amount of smoothing applied to the input frame 224 withrespect to the output 222 of the non-linear smoothing filter λ3 220 maybe determined by using a subtraction operation 234. The output of thesubtraction operation 234 is a detail layer 3 image 244. The detaillayer 3 image 244 includes the differences between the output 222 of thenon-linear smoothing filter λ3 220 and the output 212 of the non-linearsmoothing filter λ2 210.

Additional comparisons may be included relative to different images,combinations of images, filtered and non-filtered images, as desired. Asit may be observed, each of the different subtraction operations 230,232, 235, identifies a different amount of noise that was removed as aresult of one or more non-linear smoothing filters. Thus, the techniqueindicates different amounts of noise that exists as a result ofdifferent amounts of applied smoothing. In this manner, the system hasavailable to it a set of output images indicating the effects of thedifferent amounts of smoothing applied thereto, without having topre-process the image content to determine a particular smoothing filterto be applied at the exclusion of other smoothing filters. In addition,the arrangement of a plurality of different non-linear smoothingfilters, each using the same input frame, is suitable for parallelprocessing. Also, the arrangement of a plurality of differentsubtraction operations, each using a different sets of input, aresuitable for parallel processing, and at least partially temporallyoverlapping processing for the same input frame. Additional subtractionoperations (or otherwise) may be included, if desired.

The detail layer 1 image 240 may be provided to a non-linear smoothingfilter σ1 250. The non-linear smoothing filter σ1 250 reduces the noisein the resulting detail layer 1 based upon the image content, noiselevels, etc. The output of the non-linear smoothing filter σ1 250 is asmoothed layer 1 260.

The detail layer 2 image 242 may be provided to a non-linear smoothingfilter σ2 252. The non-linear smoothing filter σ2 252 reduces the noisein the resulting detail layer 2 based upon the image content, noiselevels, etc. The output of the non-linear smoothing filter σ2 252 is asmoothed layer 2 262.

The detail layer 3 image 244 may be provided to a non-linear smoothingfilter σ3 254. The non-linear smoothing filter σ3 254 reduces the noisein the resulting detail layer 3 based upon the image content, noiselevels, etc. The output of the non-linear smoothing filter σ3 254 is asmoothed layer 3 264.

The non-linear smoothing filters 250, 252, and 254 are preferablydifferent filters suitable for the corresponding non-linear smoothingfilters 202, 210, and 220. In some cases, the non-linear smoothingfilters 250, 252, and 254 are the same filter. The non-linear smoothingfilters an are suitable for parallel processing, where the same inputimage may be at least partially be temporally processed in parallel.Additional non-linear smoothing filters may be included, if desired.

The output of the non-linear smoothing filters 250, 252, 254 may beprovided to an adjustment process 270. The adjustment process 270 maybe, for example, a gamma correction. The adjustment process 270 mayresult in a noise reduction because primarily (or substantially) onlythe residual noise content is being adjusted. For example, theadjustment process 270 may selectively not amplify smaller values to thesame extent as larger values. In addition, adjustment of the residualnoise facilitates selective limiting the amount of the enhancement sothat a suitable multiplier can be limited for stronger details to reducethe effects of clipping. The adjustment process 270 may provide the sameadjustment to each of the outputs of the non-linear smoothing filters250, 252, and 254 or it may be different for one or more of suchoutputs.

The output of the adjustment process 270 may be corresponding adjustedimages 272, 274, 276 for each of the input images 260, 262, 264. Witheach of the adjusted images 272, 274, 276 being a portion of theoriginal input frame 200 they may be summed together to provide thenoise related image content that was subtracted from the original inputframe 200. In addition, the output of the non-linear smoothing filter λ1204 is also added to the output of the adjustment process 270 to providean enhanced output image 280.

Any suitable filer or a selection of different filters may be used forthe non-linear smoothing filters 202, 210, 220. For example, thenon-linear smoothing filters may be a bilateral filter, a weighted leastsquare filter, and/or a guided filter. In general, the filterspreferably reduce the modification of image content near an edgerelative to areas that are not as near to such an edge. In this manner,the output of the adjustment process 270 near an edge is small or nearzero since there is limited need for changes in regions proximate anedge. Thus for regions near an edge the output of the adjustment process270 is zero or otherwise near zero and therefore the adjustment process270 will not significantly boost such edges. Without excessively boostededges the overshooting problem near edges will not substantially occur.

The preferred implementation of the system uses a 1-dimensionaloperation on the image content.

Referring to FIG. 3, a modified technique includes receiving input videoframes 400. An edge preserving filter 410 may receive each input frame400. Preferably, the edge preserving filter 410 is a single channelfilter. The edge preserving filter 410 attenuates the image to a greaterextent in regions that are not proximate an edge than in the regionsproximate the edge. Therefore, the non-edge regions of the image tend tobe small or otherwise zero. The modified technique determines thedifference 420 between the input frame 400 and the edge preservingfilter 410. The result of the difference 420 is to provide a differenceframe where the edge regions of the image are small or otherwise zero.Since the edge regions are typically those that would otherwise resultin undesirable artifacts if boosted, the attenuation of the edge regionsreduces the likelihood of such artifacts during subsequent processing.The output of the difference 420 is enhanced by an enhancement process430. For example, the enhancement process may multiple the values by avalue or by a linear and/or non-linear function. The enhancement process430 may further be modified by a user input, if desired. The enhancementprocess 430 may be based upon the content of the image, if desired.Preferably, the enhancement process 430 is not based upon the content ofthe image to determine the filtering to be applied. The output of theenhancement process 430 is combined 440 with the input frame 400. Thecombination 440 may be a summation process, if desired. The output ofthe combination 440 is the enhanced output image 450.

The terms and expressions which have been employed in the foregoingspecification are used therein as terms of description and not oflimitation, and there is no intention, in the use of such terms andexpressions, of excluding equivalents of the features shown anddescribed or portions thereof, it being recognized that the scope of theinvention is defined and limited only by the claims which follow.

I/We claim:
 1. A method for enhancing an input image comprising: (a)receiving an input image; (b) filtering said input image with a firstnon-linear smoothing filter to provide a first filtered output; (c)filtering said input image with a second non-linear smoothing filter toprovide a second filtered output; (d) filtering said input image with athird non-linear smoothing filter to provide a third filtered output;(e) processing said input image and said first filtered output todetermine a first detail layer; (f) processing said first filteredoutput and said second filtered output to determine a second detaillayer; (g) processing said second filtered output and said thirdfiltered output to determine a third detail layer; (h) filtering firstdetail layer with a fourth non-linear smoothing filter to provide afirst smoothed layer based upon the content of said first detail layer;(i) filtering said second detail layer with a fifth non-linear smoothingfilter to provide a second smoothed layer based upon the content of saidfirst detail layer; (j) filtering said third detail layer with a sixthnon-linear smoothing filter to provide a third smoothed layer based uponthe content of said first detail layer; (k) adjusting said first,second, and third smoothed layers in such a manner that regions closerto an edge are enhanced to a lesser extent than regions farther from anedge; (l) combining said adjusted said first, second, and third smoothedlayers to provide an enhanced output image.
 2. The method of claim 1wherein said first, second, and third non-linear smoothing filters havean increasing amount of filtering.
 3. The method of claim 2 wherein saidprocessing of (1) said input image and said first filtered output is adifference operation, (2) said first filtered output and said secondfiltered output is a difference operation, and (3) said second filteredoutput and said third filtered output is a difference operation.
 4. Themethod of claim 3 wherein said first smoothed layer, said secondsmoothed layer, and said third smoothed layer have an increasinglyamount of smoothness applied with respect to said input image.
 5. Themethod of claim 4 wherein said adjusting is a gamma process.
 6. Themethod of claim 5 wherein said combining is a summing operation.
 7. Themethod of claim 6 wherein said fourth, fifth, and sixth non-linearsmoothing filters are the same filter.
 8. The method of claim 1 whereinsaid filtering said input image with said first, second, and thirdnon-linear filters is performed in a parallel manner.
 9. The method ofclaim 1 wherein (1) said processing said input image and said firstfiltered output to determine said first detail layer, (2) saidprocessing said first filtered output and said second filtered output todetermine said second detail layer, and (3) said processing said secondfiltered output and said third filtered output to determine said thirddetail layer is performed in a parallel manner.
 10. The method of claim1 wherein said filtering said input image with said fourth, fifth, andsixth non-linear filters is performed in a parallel manner.
 11. Themethod of claim 1 wherein said combining said first, second, and thirdsmoothed layers further includes said first filtered output to providesaid enhanced output image.
 12. A method for enhancing an input imagecomprising: (a) receiving an input image; (b) filtering said input imagewith a plurality of non-linear smoothing filters providing a respectiveplurality of filtered outputs; (c) processing a plurality of saidfiltered outputs with respect to at least one of another of saidfiltered outputs and said input image to determine a plurality of detaillayers; (d) filtering said plurality of detail layers with a pluralityof non-linear smoothing filters providing a respective plurality ofsmoothed layers; (e) adjusting said plurality of smoothed layers in sucha manner that regions closer to an edge are enhanced to a lesser extentthan regions farther from an edge; (f) combining said adjusted saidsmoothed layers to provide an enhanced output image.
 13. The method ofclaim 12 wherein said filtering said input image with said plurality ofnon-linear smoothing filters providing said respective plurality offiltered outputs have an increasing amount of filtering.
 14. The methodof claim 13 wherein said processing is a difference operation.
 15. Themethod of claim 14 wherein said plurality of smoothed layers have anincreasingly amount of smoothness applied with respect to said inputimage.
 16. The method of claim 15 wherein said adjusting is a gammaprocess.
 17. The method of claim 16 wherein said combining is a summingoperation.
 18. The method of claim 12 wherein said combining smoothedlayers further includes one of said first filtered outputs to providesaid enhanced output image.